EMA Cross Over Trend Following Strategy with ATR Dynamic Stop Loss Optimization

Pine ScriptTrend following Breakout Mean reversion EMA ATR ADX / DMI

Author: ianzeng123
Complexity: Starter · 63 lines
Parameters: 0
Backtest bar: 1d · swing
Tested on: ETH/USDT · spot

Jump to code View in vault Original on FMZ

Overview

This strategy is a trend-following system based on moving average crossovers and dynamic stop-loss management. The core logic is to capture the beginning of uptrends through the golden cross of fast moving average (EMA5) and slow moving average (EMA200), combined with ATR-based dynamic stop-loss for profit protection. The strategy also incorporates a fixed percentage take-profit target to balance risk and reward.

Strategy Principles

The strategy operates on the following core mechanisms:

Entry signals are triggered when EMA5 crosses above EMA200, indicating short-term momentum breakthrough
Dynamic stop-loss is calculated based on the ATR indicator, set at close price minus ATR value multiplied by a factor
Take-profit target is set at a fixed percentage (default 5%) above entry price
During position holding, ATR stop-loss moves up with price movement, forming a trailing stop
The strategy automatically closes positions when price hits either stop-loss or take-profit levels

Strategy Advantages

Strong trend capture capability - EMA crossover system effectively identifies early trend stages
Flexible risk management - ATR dynamic stop-loss adapts to market volatility
Stable execution - Systematic entry and exit rules avoid emotional interference
High parameter adaptability - Moving average periods, ATR multiplier, and take-profit percentage can be optimized
Clear operational logic - Strategy rules are simple and easy to understand and execute

Strategy Risks

False breakout risk - Ranging markets may produce multiple invalid cross signals
Drawdown risk - Sudden trend reversals may lead to significant drawdowns
Slippage risk - Stop-loss or take-profit orders may face slippage in volatile markets
Parameter sensitivity - Optimal parameters may vary significantly across different market conditions
Money management risk - Fixed position sizing may be too risky in certain situations

Strategy Optimization Directions

Add trend filters - Incorporate trend strength indicators like ADX to filter weak trends
Optimize stop-loss mechanism - Consider combining support levels or volatility percentages
Dynamic take-profit adjustment - Adjust take-profit targets based on market volatility or trend strength
Add time filters - Avoid highly volatile time periods
Improve position management - Introduce dynamic position sizing based on market risk levels

Summary

This is a trend-following strategy combining classic technical indicators with modern risk management. It captures trends through moving average crossovers and protects profits using ATR dynamic stop-loss, performing well in trending markets. While there are risks of false signals, strategy stability can be significantly improved through parameter optimization and additional filters. The core advantages lie in its systematic operational logic and flexible risk management mechanism, making it suitable as a foundation framework for medium to long-term trend trading.

Source Pine Script

/*backtest
start: 2024-02-21 00:00:00
end: 2025-02-18 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Binance","currency":"ETH_USDT"}]
*/

// -----------------------------------------------------------
//  Title:    EMA5 Cross-Up EMA200 with ATR Trailing Stop & Take-Profit
//  Author:   ChatGPT
//  Version:  1.1 (Pine Script v6)
//  Notes:    Enter Long when EMA(5) crosses above EMA(200).
//            Exit on either ATR-based trailing stop or
//            specified % Take-Profit.
// -----------------------------------------------------------

//@version=6
strategy(title="EMA5 Cross-Up EMA200 ATR Stop", shorttitle="EMA5x200_ATRStop_v6", overlay=true, initial_capital=100000, default_qty_type=strategy.percent_of_equity,default_qty_value=100)

// -- 1) Inputs
emaFastLength   = input.int(5,    "Fast EMA Length")
emaSlowLength   = input.int(200,  "Slow EMA Length")
atrPeriod       = input.int(14,   "ATR Period")
atrMult         = input.float(2.0,"ATR Multiplier", step=0.1)
takeProfitPerc  = input.float(5.0,"Take-Profit %", step=0.1)

// -- 2) Indicator Calculations
emaFast   = ta.ema(close, emaFastLength)
emaSlow   = ta.ema(close, emaSlowLength)
atrValue  = ta.atr(atrPeriod)

// -- 3) Entry Condition: EMA5 crosses above EMA200
emaCrossUp = ta.crossover(emaFast, emaSlow)

// -- 4) Determine a dynamic ATR-based stop loss (for trailing)
longStopPrice = close - (atrValue * atrMult)

// -- 5) Take-Profit Price
//    We store it in a variable so we can update it when in position.
var float takeProfitPrice = na
var float avgEntryPrice   = na

if strategy.position_size > 0
    // If there is an open long, get the average fill price:
    avgEntryPrice   := strategy.position_avg_price
    takeProfitPrice := avgEntryPrice * (1 + takeProfitPerc / 100)
else
    // If no open position, reset
    takeProfitPrice := na
    avgEntryPrice   := na

// -- 6) Submit Entry Order
if emaCrossUp
    strategy.entry(id="Long", direction=strategy.long)

// -- 7) Submit Exit Orders (Stop or Take-Profit)
strategy.exit(id         = "Exit Long",stop       = longStopPrice,limit      = takeProfitPrice)

// -- 8) (Optional) Plotting for Visuals
plot(emaFast, color=color.new(color.yellow, 0), linewidth=2, title="EMA Fast")
plot(emaSlow, color=color.new(color.blue,   0), linewidth=2, title="EMA Slow")
plot(longStopPrice, color=color.red, linewidth=2, title="ATR Trailing Stop")

Published by ianzeng123 on the FMZ strategy square · last modified 2025-02-27. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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